Energy consumption is one of the worst aspects of blockchain technology like cryptocurrencies and NFTs. Most blockchains need computers to continuously do meaningless calculations, at a time when we should be using as little power as possible.
Blockchains should be based on real-world computations, which is something we may have to do in the future. In order for a blockchain’s math to work, it must have a very unique property: the answer must be complex to compute yet simple to verify. A number of relevant computations have been found as suitable alternatives for the ones now utilised in a large number of system implementations.
A new possibility has emerged in a report published just this week. Although optimization issues are famously expensive in terms of calculations, it is very straightforward to judge the quality of a solution. A modest energy grid is being optimised in this example, which might somewhat balance the energy use of a blockchain.
Optimization
When it comes to computing, factoring huge numbers that are the product of two prime numbers is one example that makes sense in blockchain. Identifying two primes is computationally challenging, but once you have them, multiplying them is a cinch. Non-trivial calculations are worthless unless you have a specific application for them, which is why they’re not worth the effort.
Optimization challenges are much the same. In order to get the best answer, such as the shortest route that covers many cities, one must sample all feasible routes. With each new destination on the schedule, the number of possible paths grows exponentially. Many optimization issues, however, are significantly easier to test since determining if a suggested path is efficient is a lot simpler computation.
When it comes to real-world applications, optimization issues are everywhere, from how to fit as many boxes into a shipping container to how to distribute equipment and specialists so that maintenance work may be completed in the most effective way possible. To make this change from a proof-of-work (PoW) to a proof-of-solution (PoSo) model, a group of researchers is working to prove the usefulness of blockchain transactions. Drop the letter and think about it if you want to know how PoSo came up with a second “o.”)
The researchers used irony as their optimization issue for their PoSo blockchain, concentrating on how much energy other blockchains consume. For example, they observe that there are various issues with energy distribution that may benefit from optimization, including matching supply with demand and determining the best cost-effective way to combine different power generation sources.
In addition, they believe that the energy industry is becoming more decentralised, with more goods like microgrids, rooftop solar, intermittent power sources, and smaller on-grid batteries all decentralising the sources of on-grid power, making blockchain a better fit for the future. PoSo-based optimizations might let sub-grids govern themselves instead of relying on a single, centralised grid, according to the researchers.
Is there no longer a need for Enrons?
They use two modest energy systems to test their technology. One example is the University of Manchester, which includes a number of cogeneration plants, electrical storage, and thermal storage, in addition to a number of boilers, all of which work in concert. Although this is a complex economic optimization issue, it can be solved in less than 220 seconds. It takes exactly one second to verify that solution.
For the city of Suzhou, China, they analysed a system that delivers energy, heating, and cooling for a whole district. For the allocation of resources, the system was able to outperform a centralised management system in terms of speed and efficiency once more.
When numerous computers are needed for computations and verification, it consumes more energy than if the optimization were performed on only one machine. PoSo’s researchers, on the other hand, contend that it offers an important advantage: It’s more difficult to play.
Imagine a scenario in which the operator of the central management system wishes to prioritise certain producing sources, even though they are more expensive than other possibilities. There is virtually no way to halt it. In a distributed system, on the other hand, each node competes with the others to discover the optimal answer. One or two nodes may have been hacked, but the verification procedure ensures that at least one of these will be utilised.
As a whole, this seems like a stretch because it’s not obvious how often energy prices are manipulated in this way. Some specific ideas on the use of blockchain in circumstances where the energy needs aren’t horrible and there are meaningful practical consequences are still wonderful to see in this space.
